Gender inequality remains a defining feature of global social structure and an enduring barrier to equitable health outcomes. According to the World Health Organization [1], gender has implications for healthcare across all aspects of a person’s life, from access to preventive services to the quality of treatment received for chronic conditions. Although progress in women’s education, political participation, and economic opportunities has been documented across most world regions, persistent inequalities continue to shape differential health experiences and outcomes between men and women [2]-[4]. Research demonstrates that gender inequalities in healthcare stem from the primary inequality between men and women that is prevalent in many cultures [5][6]. The Platform for Action rightfully emphasizes that the existence of economic servitude and poverty and economic subjugation of women, violence against women, historically hostile viewpoints toward the female gender, discrimination by race, employment and income levels, the limited control women may have over their sexual and reproductive rights, and the powerlessness and vulnerability in all walks of life are the truths that negatively impact women’s health [7][8]. Women ought to have the right to the best quality of overall health, which is requisite not only to their individual lives and general contentment but also to being actively involved in all aspects of society [9][10].

However, healthiness and contentment have been deprived for most women globally. Good health represents an equilibrium across all aspects of contentment and is not merely the absence of adverse health conditions [10]. A major obstacle is the inequality between genders and within genders across various ethnicities, countries, and locations. Major policy forums have affirmed that to achieve greater health throughout one’s lifespan, equality in sharing family obligations, progress, and tranquility is required [7][8].

Despite this normative recognition, both healthcare providers and consumers have hardly been alerted to the consequences of “gender” in deliberating how the delivery and caliber of healthcare are identified and evaluated. Gender describes not only the biological differences but also the sharply varying roles in culture and society between traditionally defined men and women, including the assumptions and limitations imposed on their respective functional responsibilities. Researchers from diverse entities and fields have recently highlighted significant gender disparities in accessing healthcare services and in the provision and quality of care received [11]-[13]. Gender encompasses both biological differences and the distinct roles in culture and society between traditionally defined men and women, including the assumptions and limitations imposed on their respective functional responsibilities [14]. It is generally accepted in epidemiology and the sociology of health that in developed countries, men have a shorter lifespan than women, but women experience greater malaise than men [15]-[17]. Numerous arguments have been proposed and tested regarding differences in risks associated with biases and discrimination in healthcare. Several studies have revealed that the directions of gender inequities in health-related conditions are more complex than traditionally understood [18]-[20]. The trends and immensity of gender-related disparities in health vary depending on the prevailing indications or observations, as well as the stage of the life cycle [17][21]. Gender inequality has been found to be persistent during the entire life cycle for affliction in psychological issues, but less pronounced or contradictory for many physical indications.

Despite this normative recognition, the empirical relationship between gender inequality and women’s health outcomes remains complex and context dependent. While macro-level indices such as the Gender Inequality Index (GII) and Global Gender Gap Report highlight patterns of inequality, few studies systematically examine how specific domains of gender inequity—education, employment, political participation, and personal safety—translate into measurable health outcomes across countries and over time [22][23]. Moreover, even where gender parity has advanced in access, the quality and safety of participation (e.g., work environments, exposure to pollutants, political violence) often remain unaddressed [24][25].

This study examines how gender inequality across multiple societal dimensions affects women’s health outcomes globally. Drawing upon 13 years of panel data from 116 countries, the analysis investigates whether improvements in gender parity correlate with reductions in female mortality, increases in life expectancy, and lower HIV incidence among women. Using general linear modeling (GLM) with fixed effects for year and country, this study assesses the magnitude and direction of these associations while accounting for key confounders such as national wealth (GDP per capita), fertility rate, immunization coverage, and population size. The study’s significance lies in integrating quantitative data analysis with theoretical frameworks that capture the institutional and structural underpinnings of gender inequality. While most existing cross-national studies rely on composite indices, this paper disaggregates gender inequality into education, economic opportunity, political representation, and personal safety, offering a more granular understanding of how distinct inequities shape health outcomes. The study is guided by the following overarching research question:

Is there an association between gender inequality across education,economic,political,and personal safety domains and adverse health outcomes for women across countries?

The contribution of this study is threefold. First, it empirically extends the Capability Approach [24][26] by quantifying how institutional inequalities limit women’s realized capabilities in terms of health and longevity. Second, it integrates Institutional Theory to explain how national structures and governance could mediate gender-health linkages [27]. Third, it introduces a public health policy perspective grounded in the Social Determinants of Health framework [28], connecting socioeconomic and political determinants to measurable epidemiological outcomes.

The remainder of this paper proceeds as follows. Section 2 develops the theoretical basis, linking gender inequality to institutional and capability perspectives on health. Section 3 presents a literature review synthesizing prior empirical and conceptual work. Section 4 describes the variables and hypotheses with their rationales. Section 5 outlines the methodology, including data sources, model specifications, and analytic procedures. Section 6 presents results and analysis, incorporating statistical tables and providing an interpretation of the findings. Section 7 discusses implications, scope and limitations, and future research directions, followed by conclusions and references.

Understanding the complex linkages between gender inequality and female health outcomes requires a grounding in multiple, complementary theoretical perspectives. This study draws primarily on Sen’s Capability Approach, Institutional Theory, and the Social Determinants of Health (SDH) framework. Together, these perspectives articulate how individual agencies, institutional structure, and systemic social determinants intersect to shape women’s health globally [29].

Amartya Sen’s Capability Approach (1999) provides a normative and analytical framework for understanding well-being not merely in terms of resources or utilities but as the substantive freedoms—capabilities—that individuals possess to live the lives they value [24]. Health is both an intrinsic capability and an instrumental one, enabling participation in economic, educational, and political life [26]. Gender inequality constrains these freedoms through unequal access to education, employment, safety, and political voice. In contexts where women face institutional or cultural barriers, even improvements in income or education do not necessarily translate into enhanced health outcomes. Sen emphasizes that conversion factors—such as social norms, discrimination, and bodily integrity—mediate the transformation of resources into capabilities. Hence, gender inequality represents both a deprivation and a mechanism perpetuating multidimensional disadvantages.

In this study, gender inequality in education, economic participation, political representation, and personal safety is conceptualized as a restriction on women’s capabilities. Their cumulative effects manifest in health outcomes, particularly mortality, life expectancy, and HIV incidence, which are themselves reflections of realized well-being. In this capability framework, gender inequality manifests as systematic restrictions on freedoms that prevent women from achieving optimal health. As Sen and Ostlin (2007) articulated, enhancing gender equity in healthcare and articulating women’s rights to healthcare are two key strategies to mitigate overall disparities and ensure fair and equitable healthcare delivery [30]. The capability approach helps explain why even in contexts where women have gained access to education or employment, health outcomes may not improve proportionally—the conversion of these resources into health capabilities depends on the absence of gender-based restrictions and the presence of supportive institutional environments.

Women have historically faced a stereotypical perception of being the primary care provider, as well as an excessive user of healthcare services in the family. The aspirations and realities of women’s economic and social conditions differ considerably from those of men, and therefore, their overall demands and rights regarding healthcare delivery are also vastly different. In clinical practice, women are generally perceived to fall ill more frequently under the assumption that they face additional reproductive health problems and inexplicable emotional or physical health issues [21][31][32]. Even with these presumed ubiquitous traits, major dissimilarities persist among women, differentiated by age, culture, job status, ethnicity, motherhood, race, sexual preference, and socio-economic strata, among others [33][34]. Historically, healthcare providers and key players have overlooked the fact that women are an eclectic group with clearly delineated aspirations and demands [17][35][36]. Research has highlighted systemic inequalities and underscored the need for targeted interventions to address health inequities [37][38].

Institutional Theory complements the capability framework by emphasizing the rules, norms, and structures that shape social behavior and constrain agency [27]. Institutions—both formal (laws, policies) and informal (norms, traditions) mediate gendered access to opportunities and resources. For example, labor laws governing maternity protection, equal pay, and workplace safety are institutional levers that influence women’s occupational health and economic security [39]. In the context of this study, national institutions are treated as contextual moderators: even with similar levels of gender parity in education or employment, institutional quality determines whether these gains translate into improved health outcomes. Weak regulatory environments can expose women to occupational hazards or limit access to health care, undermining the benefits of equality in participation [40]. The findings that gender equality in education and employment correlate paradoxically with lower life expectancy (see Section 6) reflect precisely these institutional failures—where participation without protection exacerbates exposure to risks.

The Social Determinants of Health (SDH) framework [28][29] situates health outcomes within the broader context of social hierarchies and economic structures. Gender operates as a structural determinant, intersecting with class, ethnicity, and geography to shape exposure and vulnerability to disease. The framework distinguishes between structural determinants (e.g., governance, policy, socioeconomic position) and intermediary determinants (e.g., living conditions, behaviors, psychosocial factors). Gender inequality in education, employment, and politics constitutes a structural determinant that cascades through intermediary pathways such as access to care, income security, and social participation. The SDH perspective thus reinforces the idea that health disparities are socially produced and require policy interventions beyond the biomedical domain.

Synthesizing these frameworks, this study conceptualizes gender inequality as a multidimensional structural constraint on women’s capabilities and expressed through measurable health outcomes. This framework underpins the hypotheses and operationalization of variables detailed in Sections 4 and 5.

A gender-sensitive healthcare system ought to consider the culturally and socially implemented gender differences in overall health, including curative, preventive, and reproductive healthcare, education, research, infrastructure issues, financing, and policymaking. The physiological traits and biorhythms of women and processes vary substantially from those of men, particularly in the domains of reproductive and sexual health. Likewise, the aspirations and reality in the economic and social conditions of women differ considerably from those of men [41]-[43]. A healthcare delivery system that is perceptive to women is essential, as women generally cope with health issues that are vastly different from those of men. Further, even if they face the same issues as men, they are likely to be affected in different ways [44]-[46]. The physiological traits, processes, and biorhythms of women vary substantially from those of men, particularly in the domains of reproductive and sexual health.

Research has increasingly demonstrated that gender inequalities in healthcare are vested in social aspects, while also acknowledging that males have their biological limitations [19][38]. Gender perceptions have mostly transformed, and several of these changes likely impact gender-related challenges in health and sickness. An affirming possibility is that gender inequalities in healthcare have changed over time [4][30][41]. Gender inequalities refer to the different treatment of men and women, resulting in the methodical empowerment of men, often with adverse effects on women’s health. It is universally recognized that while the lifespan of women is longer than that of men in advanced countries, women often live it in unacceptable health [21][47][48].

Gender inequalities in healthcare are caused by the inequity in the relative financial situation and leverage of power [49] as well as the delineation of work based on sex [50]. Therefore, understanding the impact of gender inequality can help inform decision-making and shaping policies aimed at alleviating discrimination in healthcare and ameliorate the delivery and caliber of the health system, leading to better health outcomes for all individuals [51]-[54].

The empirical and theoretical literature on gender inequality and health outcomes spans public health, economics, sociology, and political science. This section synthesizes findings across these fields, emphasizing 1) global trends in gender and health; 2) sectoral dimensions of inequality; and 3) methodological advances in cross-national analysis.

Empirical studies have consistently shown that gender inequality undermines population health [23][55]. Countries with lower GII scores tend to have higher female life expectancy and lower maternal mortality [56]. However, aggregate indices often mask domain-specific disparities. For instance, Sub-Saharan Africa exhibits improving education parity but continues to report the world’s highest female HIV incidence [57]. Similarly, South Asia has narrowed gender gaps in schooling but lags in women’s labor force participation and safety [22]. Cross-national studies by Pörtner et al. (2018) and Shannon et al. (2019) confirm that gender equality is positively correlated with female health outcomes, yet the magnitude and direction of relationships vary by context [58][59]. In many developing countries, improvements in education do not immediately translate into better health due to systemic poverty, cultural constraints, and weak public health infrastructure.

Education enhances women’s health literacy, decision-making, and access to health services [60]. However, the returns to education depend heavily on institutional quality and economic structure. In industrialized nations, higher female education correlates with longer life expectancy [61], while in lower-income settings, early entry into unsafe labor markets or poor healthcare access can offset these gains [62]. Moreover, education fosters intergenerational benefits—educated women tend to have fewer, healthier children [63]. Yet, in societies where gender norms restrict autonomy, education alone may not yield proportional health benefits [64]. These findings align with the current study’s mixed results on education parity, suggesting that educational access without empowerment is insufficient for improving health outcomes.

Economic participation is a double-edged determinant. On the one hand, gainful employment enhances women’s autonomy and control over resources; on the other, exposure to occupational hazards, informal labor, and economic stress can deteriorate their health [65][66]. Studies in manufacturing sectors of developing economies reveal that women often face unsafe working conditions, limited healthcare, and gender-based pay gaps [67]. Cross-national evidence shows that women’s employment correlates with improved family nutrition and child health but may increase psychosocial stress and chronic disease risk if unaccompanied by labor protections [68]. These dynamics explain why economic opportunity parity, while desirable, may paradoxically be associated with lower female life expectancy when structural inequities persist.

Women’s political empowerment is increasingly recognized as a determinant of health policy priorities [69]. Countries with higher proportions of women in parliament exhibit greater investment in health and social welfare [69]. Political representation not only enhances women’s voice but also shapes legislation around maternal care, HIV prevention, and gender-based violence. Empirical analyses by [70][71] show that political gender parity is associated with lower female mortality and higher immunization rates. In this study, political representation emerged as a significant predictor of reduced female HIV incidence, underscoring the policy-mediating role of women’s agency in governance.

Personal safety here is associated with only personal health safety and healthcare equity is foundational to health equity. For example, access to HIV treatment represents a critical indicator of gendered safety and healthcare reach [57]. Countries where women have equitable access to antiretroviral therapy report lower HIV incidence and better life expectancy. However, barriers such as stigma, geographic isolation, and weaknesses in the health system persist [29].

Prior cross-national studies have typically employed composite indices such as the Gender Development Index or GII to test correlations with macro-level health outcomes [72]. While useful for global comparisons, these indices often obscure causal mechanisms and domain-specific dynamics. Few studies disaggregate gender inequality into specific dimensions—education, employment, politics, and safety—and examine their unique associations with health outcomes over time. This study advances the field by employing a 13-year panel dataset across 116 countries, disaggregating inequality dimensions, using General Linear Models controlling for both country and temporal effects, and testing multiple dependent variables (mortality, life expectancy, HIV incidence). The following section operationalizes these constructs, presenting variables, measurement rationale, and hypothesis development.

Drawing on the theoretical framework, the following research model (Figure 1) and hypotheses are proposed to examine how gender inequality in each domain relates to women’s health outcomes. Each main hypothesis comprises four sub-hypotheses corresponding to the four dimensions of gender inequality.

Figure 1. Conceptual framework linking gender inequality to female health outcomes.

This study employs a quantitative, cross-national panel design to analyze the relationship between gender inequality and female health outcomes over time. The empirical model integrates cross-sectional and longitudinal variation, allowing for robust estimation of structural effects while controlling for unobserved country- and year-specific heterogeneity. Data were drawn from the World Bank’s World Development Indicators (WDI) for the period 2007-2019, encompassing 116 countries with balanced data coverage. This 13-year window captures post-Millennium Development Goal (MDG) and early Sustainable Development Goal (SDG) implementation phases, providing a relevant temporal context for assessing progress toward gender and health equity.

All variables (Tables 1-3 above) were compiled and normalized to comparable scales to minimize multicollinearity and heteroskedasticity. Gender inequality indicators were expressed as ratios (female-to-male), ensuring comparability across countries. Dependent and control variables were standardized (z-scores) to allow direct interpretation of regression coefficients.

Bivariate correlation analysis was conducted to assess the strength and direction of relationships among variables. The results, presented in Table 4, indicate strong relationships between gender inequality variables and female health indicators, providing preliminary support for the hypothesized associations. Education parity (SchoolGPI) correlates positively with life expectancy (r = 0.53**) and negatively with mortality (r = −0.40**), consistent with theoretical expectations.

Three General Linear Models (GLM) were estimated in SPSS to test H1-H3, corresponding to each dependent variable: female mortality, life expectancy, and HIV incidence. Country and year were modeled as fixed effects to account for unobserved heterogeneity such as cultural norms, geographic factors, and global shocks. Control variables (GDP, fertility rate, immunization, total population) were included in all models.

Table 4. Correlation matrix.

Notes: **: p < 0.01 (two-tailed); *: p < 0.05 (two-tailed) thereafter.